Elements arrangement in Python

Every element of the array "data" have to be changed as follows:

For example, 4 should be seen in names_A and data_A. The names_A for 4 is 'David'. Now 'David' should be seen in names_B and data_B. The data_B for 'David' is 30. So, the element 4 must be changed by 30; and so on.

import numpy as np

names_A = ['David', 'Mark', 'Brian', 'Michael']
data_A = [4,3,1,2]

names_B = ['Mark', 'David', 'Michael', 'Brian']
data_B = [51,30,11,29]

data = np.array([[4,4,3,3,2,2,1,1,3,3],
                [4,3,3,3,2,2,3,1,3,1],
                [4,2,3,3,2,2,4,1,4,3]])

How is the easiest and simplest way of doing it?

I tried it as follows:

dats = data.ravel()

results = []
for d in dats:
    nam_A = names_A[data_A == int(d)]
    dat_B = data_B[names_B == nam_A]
    results.append(dat_B)

print np.array(results).reshape(data.shape)


[[51 51 51 51 51 51 51 51 51 51]
 [51 51 51 51 51 51 51 51 51 51]
 [51 51 51 51 51 51 51 51 51 51]]

But, it's giving wrong results. How would you do it?

Use dictionaries to create a mapping.

names_A = ['David', 'Mark', 'Brian', 'Michael']
data_A = [4,3,1,2]

names_B = ['Mark', 'David', 'Michael', 'Brian']
data_B = [51,30,11,29]

lookup_a = dict(zip(names_A, data_A))
lookup_b = dict(zip(names_B, data_B))

mapping = {value_a: lookup_b[key_a] for key_a, value_a in lookup_a.items()}

Now the keys in mapping will be the numbers from data_A with the corresponding values from data_B.

I never worked with numpy but it looks like an easy task to do the replacement now.

Just to give an example with a simple list:

data = [4, 4, 3, 3, 2, 2, 1, 1, 3, 3]
data = [mapping[value] for value in data]

data now is [30, 30, 51, 51, 11, 11, 29, 29, 51, 51].

Edited after installing numpy

If you created the mapping dictionary you can do the following:

data = np.array([[4, 4, 3, 3, 2, 2, 1, 1, 3, 3],
                 [4, 3, 3, 3, 2, 2, 3, 1, 3, 1],
                 [4, 2, 3, 3, 2, 2, 4, 1, 4, 3]])

for row in data:
    for index, value in enumerate(row):
        row[index] = mapping[value]

data is now:

[[32 30 51 51 11 11 29 29 51 51]
 [30 51 51 51 11 11 51 29 51 29]
 [30 11 51 51 11 11 30 29 30 51]]

As I never worked with numpy before there might be easier (or more pythonic) solutions, but at least this does what it should do.

来源：https://stackoverflow.com/questions/30704520/elements-arrangement-in-python

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